I like to vet my options before committing to new software but who knows if the authors are gonna support these in a month? I don’t want to waste Fable tokens to fix bugs myself when they crop up.

I have a lot of compose files in my homelab/automation setup and those are what I’m most concerned about.

Edit: 3.6 not 3.7!

Claude was definitely helpful the second time around to help with the DTS.

Is full 3D acceleration eventually possible and how's battery live?

Do you have more of these writeups?

Really curious how they did this mechanically.

e.g. the result for the 1 / [-1, 2] example doesn’t tell you how likely each value is and it clearly won’t be uniformly distributed (assuming the inputs are).

There are several Mac implementations of it that show > 2x faster Qwen3.5 already.

Taskbar, Uber, etc. cost less and have unlimited updates. How is this better?

1. understand weighted least squares and how you can update an initial estimate (prior mean and variance) with a new measurement and its uncertainty (i.e. inverse variance weighted least squares)

2. this works because the true mean hasn't changed between measurements. What if it did?

3. KF uses a model of how the mean changes to predict what it should be now based on the past, including an inflation factor on the uncertainty since predictions aren't perfect

4. after the prediction, it becomes the same problem as (1) except you use the predicted values as the initial estimate

There are some details about the measurement matrix (when your measurement is a linear combination of the true value -- the state) and the Kalman gain, but these all come from the least squares formulation.

Least squares is the key and you can prove it's optimal under certain assumptions (e.g. Bayesian MMSE).